The Scientific Computing Imaging Institute (SCI) at the University of Utah conducts original research to establish the scientific capabilities that govern the design, performance, and integration of computational tools into scientific platforms. In this position, you will be an employee of the University of Utah and have an appointment at Idaho National Laboratory. As a member of the team that spans the University of Utah, Idaho National Laboratory, and Oak Ridge National Laboratory you will provide analytical and programming expertise in the use-inspired and application of deep learning to support basic and applied research for Idaho National Laboratory.

As an experienced postgraduate researcher for the applied optimization or machine learning you will ensure that state-of-the-art methods are applied within a growing national laboratory and university team to unlock the full potential of advanced microscopy and materials characterization. You will run and lead projects in a wide variety of applications to bring about scientific and technology benefits to our team by challenging and collaborating with other scientists, professors, engineers, and business professionals on the utility and application of novel image reconstruction and analysis approaches, and spectral analysis approaches to provide ground-breaking capabilities for material science applications. You will work in interdisciplinary team comprised of scientists, engineers, and business professionals to realize the full potential and utility of deep learning for unlocking the potential revolutionary speed-ups to data access and extraction of microscopy datasets.

For example, you will improve on the utility and design of data science tools for microscopy that realize new paradigms in data acquisition, information storage, and technique development using these advanced tools and software packages. You will optimize the data science tools and developments across several installations including national laboratories and universities. Based on the development you will deploy trained models that forecast and suggest alternatives to sampling materials data for realizing the temporal, spatial, and spectral limits. Based on your developed and trained models you will discuss and present these improvements with members of top universities and national laboratories at professional conferences, meetings, and high impact peer reviewed publications. With your expertise, you will also help to identify new application areas, use cases, or technologies by applying your innovative data analytics methods and technologies. As the team is a collaboration between Idaho National Laboratory and the University of Utah, you will have the chance to actively involve yourself in the field of advanced microscopy and data science at both institutions.

Preferred Qualifications • 4 years of relevant work experience in data analysis or related field. (e.g., as a statistician / data scientist / material scientist/ physicist), including deep expertise and experience with statistical data analysis such as linear models, multivariate analysis, stochastic models, sampling methods. Analytical engagements outside class work while at school can be included. • Applied experience with machine learning on large datasets. • Experience in mathematics and algorithms. • Experience with material science and/or metallurgy. • Good communication and collaboration skills.

Type

Benefited Staff

Special Instructions Summary

Additional Information

The University of Utah is an Affirmative Action/Equal Opportunity employer and is committed to diversity in its workforce. In compliance with applicable federal and state laws, University of Utah policy of equal employment opportunity prohibits discrimination on the basis of race or ethnicity, religion, color, national origin, sex, age, sexual orientation, gender identity/expression, veteran’s status, status as a qualified person with a disability, or genetic information. Individuals from historically underrepresented groups, such as minorities, women, qualified persons with disabilities, and protected veterans are strongly encouraged to apply. Veterans’ preference is extended to qualified applicants, upon request and consistent with University policy and Utah state law. To inquire about this posting, email: This email address is being protected from spambots. You need JavaScript enabled to view it. or call 801-581-2300. Reasonable accommodations in the application process will be provided to qualified individuals with disabilities. To request an accommodation or for further information about University AA/EO policies, please contact the Office of Equal Opportunity and Affirmative Action, 201 S. Presidents Cr., Rm 135, (801) 581-8365 (V/TDD), email: This email address is being protected from spambots. You need JavaScript enabled to view it..

The University is a participating employer with Utah Retirement Systems (“URS”). To be eligible for retirement contributions, you must be hired into a benefit-eligible position. Certain new hires are automatically assigned to the URS retirement plan and other employees with prior URS service, may elect to enroll in the URS within 30 days of hire. Regardless of whether they are hired into a benefit-eligible position or not, individuals who previously retired and are receiving monthly retirement benefits from URS must notify the Benefits Department upon hire. Please contact Utah Retirement Systems at (801)366-7770 or (800)695-4877 or the University’s Benefits Department at (801)581-7447 for information.

This position may require the successful completion of a criminal background check and/or drug screen.

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